Make Sense of Edge Computing vs. Cloud Computing

The internet of things is real, and it’s a real part of the cloud. A key challenge is how you can get data processed from so many devices. Cisco Systems predicts that cloud traffic is likely to rise nearly fourfold by 2020, increasing 3.9 zettabytes (ZB) per year in 2015 (the latest full year for which data is available) to 14.1ZB per year by 2020.

As a result, we could have the cloud computing perfect storm from the growth of IoT. After all, IoT is about processing device-generated data that is meaningful, and cloud computing is about using data from centralized computing and storage. Growth rates of both can easily become unmanageable.

So what do we do? The answer is something called “edge computing.” We already know that computing at the edge pushes most of the data processing out to the edge of the network, close to the source of the data. Then it’s a matter of dividing the processing between the edge and the centralized system, meaning a public cloud such as Amazon Web Services, Google Cloud, or Microsoft Azure.

That may sound a like a client/server architecture, which also involved figuring out what to do at the client versus at the server. For IoT and any highly distributed applications, you’ve essentially got a client/network edge/server architecture going on, or — if your devices can’t do any processing themselves, a network edge/server architecture.